Fingerprinting and emission rates of particulate organic compounds from typical restaurants in Portugal

Vicente, Ana; Rocha, Sónia; Duarte, Márcio; Moreira, R; Nunes, Teresa; Alves, Célia

doi:10.1016/j.scitotenv.2021.146090

Cited by 22 publications

(13 citation statements)

References 87 publications

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“…Most recently, in measurements from the exhaust of a university kitchen, Vicente et al observed oleamide from cooking of a variety of foods, including chicken, fish, veal, and pork. They observed on the order of 0.3–6 mg oleamide/g of emitted PM 2.5 ; in the same samples, oleic acid ranged from below detection limits to roughly one order of magnitude greater than oleamide emissions . In our experiments, the mass ratios of oleamide to oleic acid for experiments with triolein and asparagine were comparable but generally higher than in these past studies, starting at 1.7 ± 0.7 (175 °C), decreasing to 0.2 ± 0.0003 (195 °C) and to 0.05 ± 0.01 (215 °C).…”

Section: Resultssupporting

confidence: 54%

Gas- and Particle-Phase Amide Emissions from Cooking: Mechanisms and Air Quality Impacts

Ditto

Abbatt

Chan

2022

Environ. Sci. Technol.

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The high-temperature cooking of protein-rich foods represents an important but poorly constrained source of nitrogen-containing gases and particles to indoor and outdoor atmospheres. For example, panfrying meat may form and emit these nitrogen-containing compounds through complex chemistry occurring between heated proteins and cooking oils. Here, we simulate this cooking process by heating amino acids together with triglycerides. We explore their interactions across different temperatures, triglyceride types, and amino acid precursors to form amide-containing products. Ammonia, arising from the thermal degradation of amino acids, may react with a triglyceride’s ester linkages, forming amides and promoting de-esterification reactions that break the triglyceride into volatilizable products. Additionally, triglycerides may thermally oxidize and fragment as they are heated, and the resulting oxygenated breakdown products may react with ammonia to form amides. We observed evidence for amide formation through both of these pathways, including gas-phase emissions of C2‑11H5‑23NO species, whose emission factors ranged from 33 to 813 μg total gas-phase amides per gram of amino acid precursor. Comparable quantities of particle-phase oleamide (C18H35NO) were emitted, ranging from 45 to 218 μg/g. The observed amide products had variable predicted toxicities, highlighting the importance of understanding their emissions from cooking and their ultimate inhalation exposure risks.

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Section: Resultssupporting

confidence: 54%

Gas- and Particle-Phase Amide Emissions from Cooking: Mechanisms and Air Quality Impacts

Ditto

Abbatt

Chan

2022

Environ. Sci. Technol.

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“…Cooking emissions are key contributors to urban aerosols (Ots et al, 2016;Vicente et al, 2021). Fatty acids are a wellestablished set of marker compounds used to track cooking emissions due to their relatively high abundance (Q.…”

Section: Introductionmentioning

confidence: 99%

The impact of molecular self-organisation on the atmospheric fate of a cooking aerosol proxy

et al. 2022

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Abstract. Atmospheric aerosols influence the climate via cloud droplet nucleation and can facilitate the long-range transport of harmful pollutants. The lifetime of such aerosols can therefore determine their environmental impact. Fatty acids are found in organic aerosol emissions with oleic acid, an unsaturated fatty acid, being a large contributor to cooking emissions. As a surfactant, oleic acid can self-organise into nanostructured lamellar bilayers with its sodium salt, and this self-organisation can influence reaction kinetics. We developed a kinetic multi-layer model-based description of decay data we obtained from laboratory experiments of the ozonolysis of coated films of this self-organised system, demonstrating a decreased diffusivity for both oleic acid and ozone due to lamellar bilayer formation. Diffusivity was further inhibited by a viscous oligomer product forming in the surface layers of the film. Our results indicate that nanostructure formation can increase the reactive half-life of oleic acid by an order of days at typical indoor and outdoor atmospheric ozone concentrations. We are now able to place nanostructure formation in an atmospherically meaningful and quantifiable context. These results have implications for the transport of harmful pollutants and the climate.

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“…The oleic-acid-ozone reaction system is a well-established model compound for heterogeneous reactions of organic aerosols due to its prevalence as a cooking emission tracer (Lyu et al, 2021;Vicente et al, 2021;Wang et al, 2020) and has been the subject of numerous experimental studies (Dennis-Smither et al, 2012;González-Labrada et al, 2007;Hearn and Smith, 2004;Hosny et al, 2013;Hung et al, 2005; King et al, 2004King et al, , 2020Knopf et al, 2005;Milsom et al, 2021b, a;Pfrang et al, 2017;Sebastiani et al, 2018;Smith et al, 2002;Woden et al, 2021;Zahardis and Petrucci, 2007). For this reason, it has been a popular system to model (Berkemeier et al, 2021;Gallimore et al, 2017;Milsom et al, 2022b;Pfrang et al, 2010Pfrang et al, , 2011Shiraiwa et al, 2010Shiraiwa et al, , 2012.…”

Section: Case Studies: Oleic-acid Ozonolysismentioning

confidence: 99%

MultilayerPy (v1.0): a Python-based framework for building, running and optimising kinetic multi-layer models of aerosols and films

et al. 2022

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Abstract. Kinetic multi-layer models of aerosols and films have become the state-of-the-art method of describing complex aerosol processes at the particle and film level. We present MultilayerPy: an open-source framework for building, running and optimising kinetic multi-layer models – namely the kinetic multi-layer model of aerosol surface and bulk chemistry (KM-SUB) and the kinetic multi-layer model of gas–particle interactions in aerosols and clouds (KM-GAP). The modular nature of this package allows the user to iterate through various reaction schemes, diffusion regimes and experimental conditions in a systematic way. In this way, models can be customised and the raw model code itself, produced in a readable way by MultilayerPy, is fully customisable. Optimisation to experimental data using local or global optimisation algorithms is included in the package along with the option to carry out statistical sampling and Bayesian inference of model parameters with a Markov chain Monte Carlo (MCMC) sampler (via the emcee Python package). MultilayerPy abstracts the model building process into separate building blocks, increasing the reproducibility of results and minimising human error. This paper describes the general functionality of MultilayerPy and demonstrates this with use cases based on the oleic- acid–ozone heterogeneous reaction system. The tutorials in the source code (written as Jupyter notebooks) and the documentation aim to encourage users to take advantage of this tool, which is intended to be developed in conjunction with the user base.

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Fingerprinting and emission rates of particulate organic compounds from typical restaurants in Portugal

Cited by 22 publications

References 87 publications

Gas- and Particle-Phase Amide Emissions from Cooking: Mechanisms and Air Quality Impacts

Gas- and Particle-Phase Amide Emissions from Cooking: Mechanisms and Air Quality Impacts

The impact of molecular self-organisation on the atmospheric fate of a cooking aerosol proxy

MultilayerPy (v1.0): a Python-based framework for building, running and optimising kinetic multi-layer models of aerosols and films

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